metadata
license: mit
base_model: xlnet/xlnet-base-cased
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: emotion_xlnet
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: validation
args: split
metrics:
- name: Accuracy
type: accuracy
value: 0.9155
emotion_xlnet
This model is a fine-tuned version of xlnet/xlnet-base-cased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.2021
- Accuracy: 0.9155
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.3639 | 0.8715 |
| 0.5892 | 2.0 | 500 | 0.2404 | 0.911 |
| 0.5892 | 3.0 | 750 | 0.2102 | 0.9175 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2